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        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        About MultiQC

        This report was generated using MultiQC, version 1.6

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        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2020-10-29, 00:24 based on data in: /rprojectnb2/infant-microbiome/work/nitsueh/rsv/fastqc_result


        General Statistics

        Showing 246/246 rows and 3/5 columns.
        Sample Name% Dups% GCM Seqs
        1103_S34_L001_R1_001
        95.8%
        52%
        0.3
        1103_S34_L001_R2_001
        95.7%
        51%
        0.3
        1104-run55_S39_L001_R1_001
        95.2%
        51%
        0.4
        1104-run55_S39_L001_R2_001
        88.2%
        52%
        0.4
        1104_S12_L001_R1_001
        87.6%
        51%
        0.0
        1104_S12_L001_R2_001
        91.6%
        52%
        0.0
        1105_S35_L001_R1_001
        93.9%
        56%
        0.1
        1105_S35_L001_R2_001
        93.5%
        55%
        0.1
        1107-run54_S38_L001_R1_001
        81.7%
        52%
        0.1
        1107-run54_S38_L001_R2_001
        68.0%
        52%
        0.1
        1107_S84_L001_R1_001
        78.9%
        51%
        0.0
        1107_S84_L001_R2_001
        72.5%
        50%
        0.0
        1112_S36_L001_R1_001
        95.3%
        50%
        0.3
        1112_S36_L001_R2_001
        95.1%
        50%
        0.3
        1113_S85_L001_R1_001
        94.8%
        55%
        0.1
        1113_S85_L001_R2_001
        95.4%
        55%
        0.1
        1117_S37_L001_R1_001
        94.4%
        52%
        0.1
        1117_S37_L001_R2_001
        94.4%
        53%
        0.1
        1117_S43_L001_R1_001
        91.7%
        52%
        0.1
        1117_S43_L001_R2_001
        94.6%
        53%
        0.1
        1118_S89_L001_R1_001
        95.6%
        54%
        0.1
        1118_S89_L001_R2_001
        94.4%
        53%
        0.1
        1119_S38_L001_R1_001
        95.2%
        53%
        0.1
        1119_S38_L001_R2_001
        94.7%
        53%
        0.1
        1121_S88_L001_R1_001
        95.1%
        54%
        0.2
        1121_S88_L001_R2_001
        94.2%
        54%
        0.2
        1124-1-run55_S40_L001_R1_001
        95.2%
        52%
        0.2
        1124-1-run55_S40_L001_R2_001
        89.7%
        53%
        0.2
        1124-1_S30_L001_R1_001
        91.2%
        52%
        0.1
        1124-1_S30_L001_R2_001
        94.1%
        52%
        0.1
        1124-2_S90_L001_R1_001
        72.6%
        52%
        0.0
        1124-2_S90_L001_R2_001
        76.7%
        52%
        0.0
        1125_S87_L001_R1_001
        95.6%
        53%
        0.1
        1125_S87_L001_R2_001
        95.2%
        54%
        0.1
        1129_S39_L001_R1_001
        95.2%
        52%
        0.1
        1129_S39_L001_R2_001
        94.6%
        52%
        0.1
        1129_S44_L001_R1_001
        93.9%
        52%
        0.2
        1129_S44_L001_R2_001
        59.1%
        53%
        0.2
        1135_S90_L001_R1_001
        94.7%
        52%
        0.2
        1135_S90_L001_R2_001
        94.5%
        51%
        0.2
        1137_S91_L001_R1_001
        95.2%
        53%
        0.1
        1137_S91_L001_R2_001
        94.9%
        53%
        0.1
        1139_S40_L001_R1_001
        95.2%
        52%
        0.1
        1139_S40_L001_R2_001
        94.6%
        51%
        0.1
        1143_S16_L001_R1_001
        90.8%
        52%
        0.1
        1143_S16_L001_R2_001
        92.8%
        52%
        0.1
        1144-1_S31_L001_R1_001
        92.5%
        53%
        0.1
        1144-1_S31_L001_R2_001
        94.6%
        52%
        0.1
        1144-2_S45_L001_R1_001
        92.9%
        53%
        0.1
        1144-2_S45_L001_R2_001
        93.4%
        52%
        0.1
        1145_S41_L001_R1_001
        95.8%
        51%
        0.1
        1145_S41_L001_R2_001
        95.6%
        53%
        0.1
        1147_S17_L001_R1_001
        93.4%
        55%
        0.1
        1147_S17_L001_R2_001
        93.3%
        54%
        0.1
        1182_S28_L001_R1_001
        91.5%
        53%
        0.2
        1182_S28_L001_R2_001
        84.7%
        53%
        0.2
        1182_S32_L001_R1_001
        94.8%
        54%
        0.1
        1182_S32_L001_R2_001
        95.9%
        56%
        0.1
        1187_S18_L001_R1_001
        92.7%
        55%
        0.1
        1187_S18_L001_R2_001
        94.0%
        55%
        0.1
        1192_S19_L001_R1_001
        92.5%
        53%
        0.2
        1192_S19_L001_R2_001
        93.5%
        52%
        0.2
        1196_S18_L001_R1_001
        95.5%
        54%
        0.3
        1196_S18_L001_R2_001
        88.7%
        54%
        0.3
        1196_S7_L001_R1_001
        93.5%
        54%
        0.1
        1196_S7_L001_R2_001
        92.4%
        53%
        0.1
        1197_S42_L001_R1_001
        97.0%
        53%
        0.4
        1197_S42_L001_R2_001
        96.5%
        53%
        0.4
        1198_S92_L001_R1_001
        96.1%
        52%
        0.1
        1198_S92_L001_R2_001
        95.3%
        51%
        0.1
        1201_S43_L001_R1_001
        93.9%
        52%
        0.1
        1201_S43_L001_R2_001
        93.6%
        52%
        0.1
        1202_S93_L001_R1_001
        95.8%
        54%
        0.1
        1202_S93_L001_R2_001
        95.6%
        55%
        0.1
        1206_S44_L001_R1_001
        95.2%
        52%
        0.1
        1206_S44_L001_R2_001
        94.9%
        52%
        0.1
        1207_S45_L001_R1_001
        96.3%
        51%
        0.3
        1207_S45_L001_R2_001
        95.5%
        52%
        0.3
        1210_S46_L001_R1_001
        96.8%
        56%
        0.1
        1210_S46_L001_R2_001
        95.8%
        56%
        0.1
        1216_S1_L001_R1_001
        92.8%
        52%
        0.2
        1216_S1_L001_R2_001
        94.6%
        51%
        0.2
        1216_S95_L001_R1_001
        93.5%
        52%
        0.1
        1216_S95_L001_R2_001
        95.1%
        51%
        0.1
        1218_S47_L001_R1_001
        90.7%
        48%
        0.1
        1218_S47_L001_R2_001
        91.1%
        51%
        0.1
        1219_S3_L001_R1_001
        93.1%
        52%
        0.1
        1219_S3_L001_R2_001
        95.7%
        53%
        0.1
        1220_S33_L001_R1_001
        93.4%
        51%
        0.3
        1220_S33_L001_R2_001
        87.7%
        52%
        0.3
        1220_S36_L001_R1_001
        89.7%
        51%
        0.1
        1220_S36_L001_R2_001
        92.5%
        52%
        0.1
        1230_S4_L001_R1_001
        91.8%
        52%
        0.1
        1230_S4_L001_R2_001
        93.1%
        52%
        0.1
        1231_S26_L001_R1_001
        93.5%
        53%
        0.1
        1231_S26_L001_R2_001
        94.6%
        51%
        0.1
        1236_S25_L001_R1_001
        91.7%
        52%
        0.2
        1236_S25_L001_R2_001
        95.1%
        52%
        0.2
        1238_S46_L001_R1_001
        94.6%
        51%
        0.1
        1238_S46_L001_R2_001
        95.9%
        52%
        0.1
        1238_S48_L001_R1_001
        95.1%
        51%
        0.1
        1238_S48_L001_R2_001
        94.7%
        52%
        0.1
        1275_S21_L001_R1_001
        95.7%
        53%
        0.3
        1275_S21_L001_R2_001
        89.0%
        52%
        0.3
        1275_S39_L001_R1_001
        93.2%
        52%
        0.2
        1275_S39_L001_R2_001
        94.1%
        52%
        0.2
        1282-1_S27_L001_R1_001
        95.8%
        54%
        0.2
        1282-1_S27_L001_R2_001
        95.6%
        56%
        0.2
        1282-2_S47_L001_R1_001
        95.1%
        54%
        0.1
        1282-2_S47_L001_R2_001
        95.6%
        56%
        0.1
        2051_S86_L001_R1_001
        95.8%
        51%
        0.1
        2051_S86_L001_R2_001
        95.4%
        52%
        0.1
        2055_S13_L001_R1_001
        91.5%
        52%
        0.1
        2055_S13_L001_R2_001
        91.9%
        52%
        0.1
        2055_S14_L001_R1_001
        93.8%
        52%
        0.2
        2055_S14_L001_R2_001
        86.2%
        52%
        0.2
        2057_S49_L001_R1_001
        95.6%
        51%
        0.3
        2057_S49_L001_R2_001
        95.7%
        52%
        0.3
        2061_S29_L001_R1_001
        92.6%
        52%
        0.2
        2061_S29_L001_R2_001
        95.1%
        52%
        0.2
        2068_S14_L001_R1_001
        91.0%
        52%
        0.2
        2068_S14_L001_R2_001
        93.6%
        52%
        0.2
        2072-1_S6_L001_R1_001
        93.9%
        53%
        0.2
        2072-1_S6_L001_R2_001
        95.2%
        53%
        0.2
        2072-2_S50_L001_R1_001
        93.5%
        53%
        0.1
        2072-2_S50_L001_R2_001
        94.9%
        53%
        0.1
        2076_S50_L001_R1_001
        94.0%
        52%
        0.1
        2076_S50_L001_R2_001
        95.0%
        52%
        0.1
        2076_S95_L001_R1_001
        95.2%
        52%
        0.8
        2076_S95_L001_R2_001
        95.8%
        52%
        0.8
        2125-1_S22_L001_R1_001
        90.6%
        53%
        0.2
        2125-1_S22_L001_R2_001
        92.8%
        53%
        0.2
        2125-2_S52_L001_R1_001
        90.6%
        53%
        0.1
        2125-2_S52_L001_R2_001
        92.2%
        53%
        0.1
        2127_S20_L001_R1_001
        93.3%
        52%
        0.1
        2127_S20_L001_R2_001
        94.3%
        51%
        0.1
        2130_S23_L001_R1_001
        93.5%
        54%
        0.1
        2130_S23_L001_R2_001
        92.7%
        54%
        0.1
        2131_S51_L001_R1_001
        95.7%
        52%
        0.1
        2131_S51_L001_R2_001
        94.7%
        52%
        0.1
        2134_S94_L001_R1_001
        94.2%
        53%
        0.1
        2134_S94_L001_R2_001
        95.0%
        53%
        0.1
        2135_S52_L001_R1_001
        95.0%
        52%
        0.3
        2135_S52_L001_R2_001
        93.7%
        52%
        0.3
        2137_S53_L001_R1_001
        95.4%
        52%
        0.1
        2137_S53_L001_R2_001
        94.3%
        51%
        0.1
        2140_S54_L001_R1_001
        94.1%
        51%
        0.1
        2140_S54_L001_R2_001
        94.5%
        52%
        0.1
        2141_S54_L001_R1_001
        91.2%
        53%
        0.2
        2141_S54_L001_R2_001
        93.0%
        53%
        0.2
        2141_S55_L001_R1_001
        91.6%
        53%
        0.1
        2141_S55_L001_R2_001
        94.1%
        53%
        0.1
        2144_S37_L001_R1_001
        93.1%
        53%
        0.1
        2144_S37_L001_R2_001
        92.9%
        52%
        0.1
        3098_S28_L001_R1_001
        92.2%
        53%
        0.1
        3098_S28_L001_R2_001
        92.6%
        52%
        0.1
        3101_S5_L001_R1_001
        92.6%
        52%
        0.2
        3101_S5_L001_R2_001
        94.0%
        52%
        0.2
        3102_S56_L001_R1_001
        94.3%
        53%
        0.1
        3102_S56_L001_R2_001
        93.2%
        53%
        0.1
        3103_S57_L001_R1_001
        95.2%
        54%
        0.1
        3103_S57_L001_R2_001
        95.4%
        53%
        0.1
        3117_S58_L001_R1_001
        93.6%
        52%
        0.1
        3117_S58_L001_R2_001
        94.9%
        51%
        0.1
        3128_S15_L001_R1_001
        93.3%
        53%
        0.2
        3128_S15_L001_R2_001
        93.0%
        53%
        0.2
        3130_S59_L001_R1_001
        95.0%
        54%
        0.1
        3130_S59_L001_R2_001
        93.6%
        53%
        0.1
        3145_S60_L001_R1_001
        93.0%
        52%
        0.1
        3145_S60_L001_R2_001
        93.4%
        52%
        0.1
        3151_S61_L001_R1_001
        95.0%
        52%
        0.1
        3151_S61_L001_R2_001
        94.7%
        51%
        0.1
        3195_S62_L001_R1_001
        95.3%
        52%
        0.1
        3195_S62_L001_R2_001
        95.4%
        53%
        0.1
        3200_S21_L001_R1_001
        90.7%
        52%
        0.1
        3200_S21_L001_R2_001
        82.4%
        53%
        0.1
        3204_S63_L001_R1_001
        93.7%
        55%
        0.2
        3204_S63_L001_R2_001
        93.5%
        53%
        0.2
        3205_S64_L001_R1_001
        95.5%
        53%
        0.1
        3205_S64_L001_R2_001
        94.6%
        53%
        0.1
        3207_S65_L001_R1_001
        94.4%
        52%
        0.1
        3207_S65_L001_R2_001
        94.9%
        51%
        0.1
        3207_S70_L001_R1_001
        91.9%
        52%
        0.1
        3207_S70_L001_R2_001
        93.8%
        52%
        0.1
        3209_S66_L001_R1_001
        95.4%
        54%
        0.1
        3209_S66_L001_R2_001
        95.1%
        53%
        0.1
        3210_S67_L001_R1_001
        94.4%
        53%
        0.1
        3210_S67_L001_R2_001
        94.0%
        54%
        0.1
        3211_S68_L001_R1_001
        94.0%
        53%
        0.1
        3211_S68_L001_R2_001
        94.5%
        53%
        0.1
        3218_S2_L001_R1_001
        91.2%
        52%
        0.1
        3218_S2_L001_R2_001
        91.2%
        52%
        0.1
        3239_S69_L001_R1_001
        95.3%
        53%
        0.1
        3239_S69_L001_R2_001
        94.4%
        52%
        0.1
        3240_S71_L001_R1_001
        93.7%
        52%
        0.1
        3240_S71_L001_R2_001
        94.2%
        52%
        0.1
        3312_S38_L001_R1_001
        93.0%
        54%
        0.1
        3312_S38_L001_R2_001
        94.0%
        54%
        0.1
        3325_S71_L001_R1_001
        95.9%
        55%
        0.1
        3325_S71_L001_R2_001
        95.9%
        55%
        0.1
        4070_S72_L001_R1_001
        94.0%
        51%
        0.1
        4070_S72_L001_R2_001
        94.1%
        52%
        0.1
        4073_S73_L001_R1_001
        95.0%
        52%
        0.1
        4073_S73_L001_R2_001
        95.3%
        52%
        0.1
        4082_S74_L001_R1_001
        93.6%
        53%
        0.1
        4082_S74_L001_R2_001
        93.0%
        52%
        0.1
        4089_S75_L001_R1_001
        93.9%
        52%
        0.1
        4089_S75_L001_R2_001
        94.7%
        52%
        0.1
        4112_S76_L001_R1_001
        94.2%
        52%
        0.1
        4112_S76_L001_R2_001
        94.7%
        52%
        0.1
        4112_S80_L001_R1_001
        93.3%
        52%
        0.2
        4112_S80_L001_R2_001
        94.9%
        53%
        0.2
        4113_S77_L001_R1_001
        95.2%
        52%
        0.1
        4113_S77_L001_R2_001
        95.0%
        52%
        0.1
        4114_S33_L001_R1_001
        86.5%
        52%
        0.1
        4114_S33_L001_R2_001
        88.3%
        52%
        0.1
        4116_S78_L001_R1_001
        90.6%
        55%
        0.1
        4116_S78_L001_R2_001
        88.7%
        53%
        0.1
        5002_S34_L001_R1_001
        92.6%
        53%
        0.1
        5002_S34_L001_R2_001
        93.4%
        54%
        0.1
        5003-1_S35_L001_R1_001
        87.5%
        51%
        0.1
        5003-1_S35_L001_R2_001
        91.9%
        51%
        0.1
        5003-2_S84_L001_R1_001
        90.5%
        51%
        0.1
        5003-2_S84_L001_R2_001
        93.4%
        51%
        0.1
        5008_S79_L001_R1_001
        95.3%
        52%
        0.1
        5008_S79_L001_R2_001
        95.4%
        52%
        0.1
        5021_S24_L001_R1_001
        92.0%
        54%
        0.2
        5021_S24_L001_R2_001
        95.3%
        54%
        0.2
        5030_S8_L001_R1_001
        92.1%
        53%
        0.1
        5030_S8_L001_R2_001
        93.1%
        53%
        0.1
        5044_S10_L001_R1_001
        92.5%
        52%
        0.1
        5044_S10_L001_R2_001
        94.7%
        53%
        0.1
        5049_S9_L001_R1_001
        93.2%
        54%
        0.1
        5049_S9_L001_R2_001
        96.2%
        55%
        0.1
        5053_S11_L001_R1_001
        91.1%
        53%
        0.1
        5053_S11_L001_R2_001
        92.8%
        52%
        0.1
        5069_S80_L001_R1_001
        95.2%
        54%
        0.1
        5069_S80_L001_R2_001
        94.8%
        55%
        0.1
        5069_S85_L001_R1_001
        91.6%
        55%
        0.1
        5069_S85_L001_R2_001
        96.1%
        56%
        0.1
        5070_S81_L001_R1_001
        93.0%
        52%
        0.1
        5070_S81_L001_R2_001
        94.4%
        51%
        0.1
        5214_S82_L001_R1_001
        93.8%
        52%
        0.1
        5214_S82_L001_R2_001
        93.4%
        52%
        0.1
        5215_S83_L001_R1_001
        93.7%
        53%
        0.1
        5215_S83_L001_R2_001
        93.9%
        52%
        0.1

        FastQC

        FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Quality Histograms

        The mean quality value across each base position in the read.

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample row to see a line plot for that dataset.
        Rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Base N Content

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Length Distribution

        The distribution of fragment sizes (read lengths) found. See the FastQC help

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Duplication Levels

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Overrepresented sequences

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as over represented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all of the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

        No samples found with any adapter contamination > 0.1%